Developing Methods to Estimate Mediation Effects in Adaptive Interventions

项目总结

PROJECT SUMMARY The proposed K01 Mentored Research Scientist Development Award will prepare Ahnalee Brincks, Ph.D. to lead the development of novel quantitative methods needed to understand the mechanisms through which person-focused adaptive interventions affect drug use and addiction (DUA), including heroin and other opioid use disorders (OUD). Dr. Brincks, Assistant Professor of Biostatistics at the Michigan State University College of Human Medicine, will benefit from the NIDA-funded establishment of MSU's Drug Dependence Epidemiology Training Program and National Hispanic Science Network Mentoring Program, continued with university support under the direction of an experienced NIDA PI, Dr. Jim Anthony, who serves as here lead K01 sponsor. Person-focused adaptive interventions (AIs) are used by clinicians make adaptations to treatment based on participant characteristics that are observed before and after treatment starts. As promising new approaches for clinical and preventive interventions in DUA and OUD, AIs give practitioners evidence-based tools to adjust an intervention to fit each patient's needs as these needs evolve, to deliver the most effective intervention at the ideal time and in the optimal dose. Current statistical approaches exist to evaluate whether AIs work and for whom AIs are effective. However, there are no statistical tools for understanding how the AIs work at the level of the person's experience, via supra-molecular mechanisms and mediational pathways investigated in clinical and prevention researchcontexts. New mediation methods are needed to improve AIs via greater understanding of intervening pathways. Identification of intervening pathways can lead to discover of new intervention targets to be challenged or confirmed in subsequent field-driving AI trials of OUD and DUA interventions. K01 support will strengthen Dr. Brincks' career development. In addition to studying OUD/DUA natural history and clinical course, diagnosis and patient care services, she also will learn 1) epidemiology as applied to DUA, their determinants and complications, defined to encompass HIV/AIDS, HCV, and other infectious diseases, 2) current DUA interventions and their hypothesized mediators, 3) experimental designs used to build adaptive interventions (e.g., Sequential Multiple Assignment Randomized Trials), and 4) state-of-the-science causal approaches to mediational pathways in NIDA research. In her K01 research, her primary aim is development of new quantitative methods to better understand mechanisms through which AIs reduce OUD and other DUA. A second aim involves applying these methods to evaluate mediation hypotheses in AI trial data. She will launch an independent program focused on OUD/DUA mediational pathways, extending current AI approaches beyond clinical intervention evaluations to focus on reducing OUD/DUA incidence rates in communities, schools, and target populations. As such, this work should have far-reaching implications for NIDA strategic goals.